文献
J-GLOBAL ID:201802287056980340
整理番号:18A1008081
胎児心拍信号と先進機械学習アルゴリズムを用いた帝王切開と正常膣分娩の分類【JST・京大機械翻訳】
Classification of caesarean section and normal vaginal deliveries using foetal heart rate signals and advanced machine learning algorithms
著者 (5件):
Fergus Paul
(Applied Computing Research Group, Department of Computer Science, Faculty of Engineering and Technology, Liverpool John Moors University, Liverpool, UK)
,
Hussain Abir
(Applied Computing Research Group, Department of Computer Science, Faculty of Engineering and Technology, Liverpool John Moors University, Liverpool, UK)
,
Al-Jumeily Dhiya
(Applied Computing Research Group, Department of Computer Science, Faculty of Engineering and Technology, Liverpool John Moors University, Liverpool, UK)
,
Huang De-Shuang
(Institute of Machine Learning and Systems Biology, Tongji University, Shanghai, China)
,
Bouguila Nizar
(Concordia Institute for Information Systems Engineering, Concorida University, Montreal, Canada)
資料名:
BioMedical Engineering OnLine (Web)
(BioMedical Engineering OnLine (Web))
巻:
16
号:
1
ページ:
89
発行年:
2017年
JST資料番号:
U7351A
ISSN:
1475-925X
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
イギリス (GBR)
言語:
英語 (EN)